DaProS: a data property specification tool to capture scientific sensor data properties

  • Authors:
  • Irbis Gallegos;Ann Q. Gates;Craig Tweedie

  • Affiliations:
  • The University of Texas at El Paso, El Paso, TX;The University of Texas at El Paso, El Paso, TX;The University of Texas at El Paso, El Paso, TX

  • Venue:
  • ER'10 Proceedings of the 2010 international conference on Advances in conceptual modeling: applications and challenges
  • Year:
  • 2010

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Abstract

Environmental scientists have begun to use advanced technologies such as wireless sensor networks and robotic trams equipped with sensors to collect data, such as spectral readings and carbon dioxide, which is leading to a rapid increase in the amount of data being stored. This has resulted in a need to evaluate promptly the accuracy of the data, the meaning of the data, and the correct operation of the instrumentation in order to not lose valuable time and information. Performing such evaluations requires scientists to rely on their knowledge and experience in the field. Field knowledge is rarely shared or reused by other scientists mostly because of the lack of a well-defined methodology for sharing information and appropriate tool support. This work presents the Data Property Specification (DaProS) tool that assists practitioners in specification and refinement of properties that can be used to check data quality. The tool can be used to capture scientific knowledge about data processes in remote sensing systems through the use of decision trees and questionnaires that guide practitioners in the specification process. In addition, the tool uses Disciplined Natural Language (DNL) property representations for scientists to validate that the specifications capture the intended meaning.